A dynamic multi-criteria decision making model with bipolar linguistic term sets

H Liu, L Jiang, L Martínez - Expert Systems with Applications, 2018 - Elsevier
Real world decision making problems under uncertainty face different challenges. These
challenges include lack of information, the necessity of quick decisions, and problems may …

Geo-uninorm consistency control module for preference similarity network hierarchical clustering based consensus model

NH Kamis, F Chiclana, J Levesley - Knowledge-Based Systems, 2018 - Elsevier
In order to avoid misleading decision solutions in group decision making (GDM) processes,
in addition to consensus, which is obviously desirable to guarantee that the group of experts …

On LAMDA clustering method based on typicality degree and intuitionistic fuzzy sets

JFB Valderrama, DJLB Valderrama - Expert Systems with Applications, 2018 - Elsevier
The learning algorithm for multivariable data analysis (LAMDA) is a learning method to
group or classify quantitative and qualitative historical data. LAMDA can be applied for self …

Application of aggregation operators for forecasting PM10 fluctuations: From available Caribbean data sites to unequipped ones

T Plocoste, S Regis, SP Nuiro, A Sankaran - Atmospheric Pollution …, 2024 - Elsevier
Air pollution is a substantial issue for public health. Predicting the levels of airborne
particles, especially those originating from natural phenomena like sand mists from the …

A data-based approach using a multi-group SIR model with fuzzy subsets: application to the COVID-19 simulation in the islands of Guadeloupe

S Regis, SP Nuiro, W Merat, A Doncescu - Biology, 2021 - mdpi.com
Simple Summary COVID-19 is a rapidly spreading and mutating pandemic. In the case of
some people the disease can be fatal It has been observed that weight and age are …

Yager–Rybalov triple Π operator as a means of reducing the number of generated clusters in unsupervised anuran vocalization recognition

C Bedoya, J Waissman Villanova… - … and Machine Learning …, 2014 - Springer
Abstract The Learning Algorithm for Multivariate Data Analysis (LAMDA) is an unsupervised
fuzzy-based classification methodology. The operating principle of LAMDA is based on …

Two cluster validity indices for the LAMDA clustering method

JFB Valderrama, DJLB Valderrama - Applied Soft Computing, 2020 - Elsevier
The learning algorithm and multivariable data analysis (LAMDA) is an algorithm to group
quantitative and qualitative data, applying self-learning and/or directed learning. Usually …

Improving the additive and multiplicative consistency of hesitant fuzzy linguistic preference relations

H Liu, L Jiang, Z Xu - Journal of Intelligent & Fuzzy Systems, 2017 - content.iospress.com
The hesitant fuzzy linguistic preference relations (HFLPRs) facilitate decision makers to
express hesitant assessments in fuzzy decision making problems. It is important for the use …

Use of fuzzy sets, aggregation operators and multi agent systems to simulate COVID-19 transmission in a context of absence of barrier gestures and social distancing …

R Sébastien, M Olivier, D Andrei - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
In this paper, we present a model of Covid-19 pandemic spreading simulated by a multi-
agent system and using fuzzy sets. This paper focuses on two risk factors: age and body …

On the reinforcement of uninorms and absorbing norms

H Le Capitainé, C Frélicot - 2016 - hal.science
Aggregation operators Reinforcement... We propose a n-ary extension of absorbing norms,
defined with the help of generative functions, and its relationship with additive generating …